最新刊期
卷 33 ， 期 2 ， 2025
- “在三维精密测量领域，专家提出了基于标定参数修正的远心三维重构模型，有效补偿测量误差，为远心光路系统精密测量提供新思路。”摘要：Telecentric imaging has the advantages of stable magnification， large depth of field and low distortion， which has attracted much attention in the field of three-dimensional precision measurement. However， due to manufacturing limitations， the aperture stop of a telecentric lens cannot be perfectly positioned at the focal plane， allowing light rays with slight angular deviations from the optical axis to enter， thereby introducing measurement errors. To address this issue， a telecentric 3D reconstruction model based on calibration parameter correction was proposed. The theoretical analysis of the causes of telecentric optical path non-ideality led to the construction of a system calibration parameter model related to the imaging depth， which compensated for the measurement error caused by optical path non-ideality. Based on the calibration parameters of the focal plane， the mathematical polynomial expression between the radial distortion coefficient and the imaging depth was established based on the control variable method and the least squares fitting algorithm. A random sampling consistency algorithm was employed to filter out the phase noise， and the phase-depth mapping relationship was established based on the polynomial model. During the process of three-dimensional reconstruction， the radial aberration coefficients were corrected based on the depth information determined from the absolute phase， thereby achieving high precision in the reconstruction of the lateral size. In the calibration plate and standard ball experiments， the measurement error of the measured line segment was reduced from 28.8 μm to 4.8 μm， and the measurement error of the diameter of the standard ball was reduced from 35.2 μm to 8.1 μm， thereby verifying the feasibility and necessity of the proposed scheme. This method provides an effective parameter correction idea for the precise measurement of the telecentric optical path system， and enriches the telecentric three-dimensional measurement technology.关键词：telecentric imaging;three-dimensional imaging;precision measurement;stripe projection profilometry0|0|0更新时间：2025-03-21
- “在机器人协同作业领域，专家提出了一种两步法手眼标定方法，显著提升了标定精度和三维拟合精度。”摘要：In order to improve the accuracy of hand-eye calibration in the cooperative operation between line laser profilers and robots， a calibration method based on the two-step method was proposed. The method utilized a commonly available calibration sphere as the calibration object， and constructed the solution equations according to the characteristic of the sphere center coordinates being constant in the robot coordinate system. By changing the attitude once and translating once in a special measurement way， the direction and position matrices were solved independently by associating the solution equations in different attitudes. The experimental results show that the standard deviations of the spherical center coordinates in the X and Y directions of the two-step method are 0.324 9 mm and 0.246 2 mm， respectively， which are 29.5% and 61.5% higher than those of the one-step method of 0.460 8 mm and 0.639 1 mm， respectively. In addition， in the sphere fitting experiments， the difference between the radius of the sphere fitted by the two-step method and the nominal radius of 14.996 mm is 0.019 mm， while that of the one-step method is 0.278 mm， which is a higher fitting accuracy of the two-step method. The two-step hand-eye calibration method proposed in this paper significantly improves the calibration accuracy and 3D fitting accuracy compared to the one-step method.关键词：hand-eye calibration;Line laser profiler;Calibration sphere;Homogeneous transformation matrix0|0|0更新时间：2025-03-21
- “在电力设备缺陷检测领域，研究人员构建了分时型红外偏振成像系统，通过控制偏振片旋转实现多通道图像采集，为提升检测准确性与效率提供新方案。”摘要：In order to improve the accuracy and efficiency of defect detection in power equipments， a time-division infrared polarization imaging system is constructed， combining a long-wave infrared detector and a polarizer. For electric transmission lines， multi-channel image acquisition is realized by controlling the polarizer rotation. Then， the polarization images with different channel numbers and different polarization angle intervals are evaluated using three parameters， i.e. root mean square error （RMSE）， peak signal-to-noise ratio （PSNR） and mean structural similarity （MSSIM）， respectively. The experimental results show that as the number of channels increases from 3 to 18， the image quality is gradually improved， especially in the range of 4 to 9 channels， where the improvement of imaging quality is most significant. However， further increasing the number of channels does not have a significant effect on the image quality， which leads to redundant calculations； for 3-channel polarization images， small angular intervals are able to capture the detailed information of fine targets， while large angular intervals are able to effectively separate the target from the background and reduce the noise interference， which are both suitable for some specific application scenarios. The experimental results are instructive for the polarization channel selection strategy of infrared polarization imaging.关键词：Power Inspection;Long-wave infrared （LWIR）;Time-division infrared polarization imaging system;Polarization channel;Stokes vector0|0|0更新时间：2025-03-21
- “报道：为提升TDLAS系统性能，研发便携式柱面镜多通池，采用NGO-VMD小波去噪算法，显著提高检测灵敏度和下限。”摘要：In order to improve the detection performance and integration of TDLAS detection system， A TDLAS system based on a portable adjustable optical path length cylindrical mirror multi-pass cell was designed， which achieved the simulated optical path length of 14 m， 10.6 m， 9.2 m， 7.1 m and 5.8 m. To reduce the impact of noise generated during gas measurement in TDLAS system on detection accuracy and sensitivity， the Variational Mode Decomposition （VMD） wavelet denoising algorithm optimized by the Northern Goshawk Optimization （NGO） was proposed. The simulation results showed that compared with other algorithms， the NGO-VMD wavelet denoising algorithm could effectively reduce noise without causing signal distortion. The performance of the system was evaluated by testing CH4 using a DFB laser with the central wavelength of 1.653 μm based on direct absorption detection technology. The results showed that the signal-to-noise ratio of the detection signal was increased from 66 to 109， and the lower detection limit of the system was improved from 12.1 ppm to 7.28 ppm. Allan analysis of variance showed that the optimal detection sensitivity of the system was improved from 641 ppb to 526 ppb at the integration time of 263 s after optimization with the NGO-VMD wavelet algorithm. The finding provided a reference for improving the performance of TDLAS trace gas detection system.关键词：Tunable Diode Laser Absorption Spectroscopy（TDLAS）;direct absorption;Adjustable optical path length;Northern Goshawk Optimization Algorithm;variational mode decomposition0|0|0更新时间：2025-03-21
Modern Applied Optics
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Development of bi-directional high overload silicon-based differential pressure sensitive element AI导读
“在传感器技术领域，研究人员设计了梁-群岛错位膜结构差压敏感元件，有效提升了双向过载能力。”摘要：In order to improve the bi-directional overload capability of differential pressure sensors， a beam-archipelago dislocated membrane structure differential pressure sensitive element was designed in this paper. The sensitive element consisted of a beam-archipelago silicon membrane structure bonded to a glass substrate. The beam structure reduced the stress concentration， and the archipelago structure improved the structural rigidity； the glass substrate was designed with square grooves and circular through holes on the bonding surface， and the dislocation structure formed by the square grooves of the silicon membrane structure and the glass substrate further reduced the maximum stress. Firstly， the stress distribution， full-scale output， and maximum stress of the bi-directional high overload silicon-based differential pressure sensitive element were analyzed using finite element software. Secondly， the relationship between structural dimensions and burst pressure was analyzed， and the structural dimensions at maximum burst pressure were solved through dimensional optimization. Finally， a silicon-based differential pressure sensitive element with bi-directional high overload was fabricated using the MEMS silicon process. The pressure test results show that the fabricated bi-directional high overload silicon-based differential pressure sensitive element has a burst pressure of 8.5 times scale， which is 30.7% higher overload capacity compared with the traditional C-type membrane structure differential pressure sensitive element （burst pressure 6.5 times scale）. The experimental results demonstrate that the beam-archipelago dislocation membrane structure can effectively improve the bi-directonal overload capacity of the differential pressure sensitive element.关键词：Micro-Electro-Mechanical System（MEMS）;Differential pressure sensitive element;finite element;size optimization;Overload capacity1|0|0更新时间：2025-03-21 - “在生物细胞工程领域，研究者设计了柔性并联压电定位台，通过建模仿真和测试，验证了其大行程、高频率运动能力，为细胞级操作提供精确定位解决方案。”摘要：In order to achieve cell-level operations such as cell capture， cutting， separation， and injection， a flexible parallel piezoelectric positioning stage for biocellular engineering was designed， modeled， simulated， and tested in this paper. The positioning stage consisted of a moving platform， a base， a three-stage amplification mechanism， and three piezoelectric actuators. The displacements generated by the piezoelectric actuators were amplified by the three-stage amplification mechanism， and the precise movement of the positioning stage was realized through feedback control， so as to achieve the target positioning effect. In the design process， the pseudo-rigid-body method combined with the flexible hinge stiffness calculation model was adopted to analyze the kinematic statics of the mechanism. The Lagrange equation was used to establish the dynamics model of the designed flexible parallel piezoelectric positioning stage using the lumped mass method. After determining the structural parameters， finite element analysis was carried out to verify the derived theoretical model， and the simulation results showed that the error between the theoretical and simulation models was less than 10%， and the mechanism was able to achieve a large stroke as well as a higher frequency of motion. In addition， a prototype system for the flexible parallel piezoelectric positioning stage was also built and experimentally tested to evaluate its open and closed loop performance. The experimental results show that the designed positioning stage has a working stroke of 125 μm×126 μm， the natural frequencies in the X-direction and Y-direction are 128.9 Hz and 132.8 Hz， and the corresponding motion resolution are both better than 400 nm， respectively.关键词：Cell micromanipulation;piezoelectric actuators;flexible parallel mechanism;micro-positioning stage0|0|0更新时间：2025-03-21
- “据最新报道，研究人员针对伺服电机位置检测精度问题，提出了一种新方法，有效提升了测量精度。”摘要：The stator slot of the servo motor led to the unequal amplitude of the output signal of the TMR （Tunneling Magnetoresistance） in two orthogonal positions. This unequal amplitude affected the measurement accuracy in the position detection theory of the servo motor based on time-gate technology. Based on the structural characteristics of the motor stator， a servo motor position detection method was proposed， which could effectively improve the precision of the motor rotor position detection. One pair of sensing probes were placed symmetrically and orthogonally on both sides of the symmetry axis of the stator teeth to achieve equal output signal amplitude. The other pair of sensing probes were positioned symmetrically and orthogonally at intervals of （2n+1）λi/2（n=0，1，…，n） degrees， which could reduce the influence of harmonic components of the magnetic field generated by the motor stator winding. Meanwhile， a waveform reconstruction method was used to eliminate the corresponding i-th harmonic component. Based on the above method， the signal amplitude was equal and the phase was orthogonal， which could effectively improve the accuracy. Simulation results demonstrated the effectiveness of the sensor structure based on the new error compensation method. The experimental results show that compared with the single pair probe which only satisfies the space orthogonal condition， the amplitude of the signal output by symmetrical structure sensors after compensation is equal， and the third harmonic component is reduced by 73.8%， The accuracy has been improved by 6 times. This method illustrates the obvious advantage in the accuracy of the motor rotor position detection.关键词：servo motor;time grating;position detection;error compensation;waveform reconstruction1|0|0更新时间：2025-03-21
Micro/Nano Technology and Fine Mechanics
- “在计算机视觉领域，研究者提出了EDFDNet去雾网络，有效提升了非均匀雾霾图像的可见性，为图像去雾研究提供了新方向。”摘要：Haze in natural environments is usually non-homogeneous and irregular， which has a large impact on computer vision tasks. Therefore， this paper proposed the Enhanced-edge-feature Dual-branch Fusion Dehazing Network （EDFDNet）. In order to retain the realism of the image and at the same time effectively improve the visibility after dehazing in the case of severe blurring， the transmission graph fine branch was constructed， which was the premier branch of the network. A U-shaped network hierarchical codec structure that fused the discrete wavelet transform was used to extract multi-scale fine feature information， and a mathematical method for the determination of the enhanced edge information was defined. The feature extraction branch tandemly connected the ResNet residual block and the Transformer combined with dual attention for a parallel feature extraction module， which fused the extracted local and global features. This improved the network's ability to understand and process non-uniform haze images and further restored the visibility of the images. These two branches were joined into the backbone framework of the Generative Adversarial Network （GAN）， and a mathematical method to strengthen the determination of edge information was defined. This formed the defogging network EDFDNet.The results of the experiments show that the average PSNR and SSIM of this method on the outdoor synthetic dataset are improved by 1.256 7 and 0.030 8， respectively， compared with the optimal results of the current mainstream methods.Meanwhile， in the test on the real-world dataset， the PIQE， RI， and VI reach the optimal indexes of 21.471， 0.971 1 and 0.900 3.EDFDNet achieves good results in both realism enhancement and visibility restoration， and is suitable for dehazing real-world non-uniform haze images.关键词：real-world haze;non-homogeneous dehazing;feature fusion;edge feature enhancement;generative adversarial network2|0|0更新时间：2025-03-21
- “在古铜镜X光图像融合领域，专家提出了一种新方法，有效保留纹饰细节和病害特征，为古铜镜保护提供新方案。”摘要：A fusion method was proposed to solve the problem that the single-energy X-ray cannot detect the complete decoration and disease information of the corroded ancient bronze mirror due to the uneven thickness of the mirror edge and the mirror center area. The method combined intuitionistic fuzzy set entropy measure and salient feature detection to fuse ancient bronze mirror X-ray images. Firstly， the effective guided filtering was introduced to enhance the contrast of the decorative structure of high-energy X-ray images. Secondly， a three-scale decomposition model was designed by using joint bilateral filtering and structure-texture decomposition strategy. The model extracted the energy layer， residual layer and detail layer information of different energy X-ray images. Then， the energy layer obtained the fused energy image through the
- “在图像融合领域，研究者提出了一种低光增强和语义注入式多尺度红外与可见光图像融合方法，有效提升了低光环境下融合图像的质量。”摘要：Aiming at the problems of unclear texture details and poor visual perception due to neglecting illumination in infrared and visible image fusion under low-light conditions， a low-light enhancement and semantic injection multi-scale infrared and visible image fusion method was proposed. Firstly， a network suitable for low-light enhancement was designed to realize the enhancement of visible images in nighttime scenes through repeated iterations of residual models. Then， a feature extractor based on the Nest architecture was used as the encoder and decoder of the network， in which the deep features could capture the complex structure and semantic information of the images. A semantic prior learning module was designed to further extract the semantic information of the deep infrared and visible images through cross-attention， and a semantic injection unit was adopted to inject the enhancement features into each scale step by step. Thirdly， a gradient enhancement branch was designed， where the mainstream features were first passed through hybrid attention， and then the Sobel operator stream and Laplacian operator stream were divided from the mainstream as a way to enhance the gradient of the fused image. Finally， the features at each scale were reconstructed by dense connections between the same layers and jump connections between different layers in the decoder. Experimental results show that this method improves the visual information fidelity， mutual information， disparity correlation coefficient， and spatial frequency， on average， by 23.1%， 16.3%， 18%， and 39.8%， respectively， in comparison with the nine methods， which effectively enhances the quality of fused images in low-light environments， and helps to improve the performance of the advanced visual tasks.关键词：infrared and visible image fusion;multiscale fusion networks;low-light enhancement;cross-attention;semantic injection2|0|0更新时间：2025-03-21
- “在水下图像增强领域，研究人员提出了融合域迁移和注意力机制的模型，有效提升了图像质量，色彩恢复更自然，细节增强效果显著。”摘要：Due to the attenuation and scattering of light in an underwater environment， the images directly captured by imaging equipment suffer from significant quality degradation. Although learning-based underwater image enhancement methods improve the original image imaging quality to a certain extent， most of the existing methods use artificially synthesized or model-generated paired datasets for training. Meanwhile， there is a large domain difference between artificial or model-generated images and real underwater images in distribution， which leads to problems of excessive enhancement and no obvious removal of color shift in the enhancement results. Focusing on these problems， an underwater image enhancement model that integrates domain transfer and attention mechanisms was proposed in this paper. First， an image generation network with domain transfer was designed and combined with the physical imaging model and the water type classifier. In this way， the feature description mapping between images in different domains and scenarios could be learned， thereby reducing the difference between the generated images and the real images. Furthermore， a multi-scale hybrid attention encoder-decoder network was designed. With the help of efficient feature connections and different attention-fused structures， the model's ability to recover local image details was improved. Finally， a global domain association consistency loss function was proposed to better train the network model parameters and improve the quality of image enhancement by constructing content and structure consistent associations of the generated images at each stage of the domain transfer. The proposed model achieved accuracies of 3.140 1， 0.602 1 and 3.076 8， 0.612 4 for the UIQM and UCIQE metrics on the underwater real datasets UIEB and EUVP， respectively. The experiments show that the proposed model could effectively improve the color recovery ability of underwater images， and more details could be recovered.关键词：underwater image enhancement;domain transfer;generative adversarial networks;Attention enhancement0|0|0更新时间：2025-03-21
- “在高端产品制造领域，针对超纤革瑕疵检测难题，MFL_YOLOv8算法显著提升了检测精度和实时性。”摘要：Microfiber leather is a high-end composite material， and its defect detection is critical for ensuring product quality. To address the challenges posed by the multi-scale， diverse aspect ratios， and numerous small defects on the surface of microfiber leather， the MFL_YOLOv8 algorithm for surface defect detection was proposed in this study. The MFL_YOLOv8 algorithm first introduced the multi-scale feature extraction module DCNv3-LKA based on the Deformable Large Kernel Attention （DLKA） mechanism， which significantly enhanced the backbone network's multi-scale feature extraction capabilities. Subsequently， the incorporation of a P2 feature map and a Dysample upsampling module in the feature pyramid network strengthened the network's ability to extract detail information from small targets. Finally， the Minimum Points Distance Intersection over Union （MPDIoU） was utilized to mitigate the inefficacy of the loss function on small targets during the initial stages of training， thus improving the detection performance for small targets. Experimental results on a self-constructed microfiber leather surface defect dataset demonstrate that the proposed algorithm achieved 92.47% of average detection precision and 92.40% of average detection recall， with improvements of 5.38% and 7.27% compared to YOLOv8n. Additionally， the algorithm attainsed a frame rate of 135.2 frames per second （FPS）， meeting the accuracy and real-time requirements for industrial applications.关键词：Microfiber leather;defect detection;DCNv3-LKA;MPDIoU2|0|0更新时间：2025-03-21
- “在视频监控和自动驾驶领域，研究人员构建了一种鲁棒的RGBT目标跟踪网络，有效克服了不利场景的影响，为相关技术发展提供了新方向。”摘要：RGBT target tracking has gained widespread application in fields such as video surveillance and autonomous driving due to its robustness and resistance to illumination and occlusion. By leveraging the common challenging attributes in infrared and visible light images and fully interacting between the two modalities， an effective tracking network was constructed， capable of overcoming the impacts of various adverse scenarios encountered during the tracking process. This network was composed of three modules： the specific attribute fusion module， the common attribute fusion module， and the cross-modality interaction module. The specific attribute fusion module enabled the network to extract modality-specific challenging attributes， effectively utilizing the advantages of different modalities. The common attribute fusion module extracted features that were matched in both modalities during target tracking and adaptively aggregated this information. It assigned corresponding weights to each common challenging attribute， thereby enhancing the tracker’s adaptability. The cross-modality interaction module incorporated common modality information into the specific modality information of infrared and visible light images， thus improving the network's robustness. To address the issue of information loss across different modalities， the traditional cross-entropy loss was optimized to enhance focus on each modality and accelerate network convergence. The proposed network is tested on the GTOT， RGBT234， and LasHeR datasets， achieving an accuracy of 84.1% and a precision of 57.3% on the RGBT234 dataset， 52.3% and a precision of 39.1% on the Lasher dataset. The results demonstrate that the tracker has achieved commendable performance， which validates the effectiveness of the proposed method.关键词：object tracking;thermal infrared tracking;challenge attributes;modal interaction2|0|0更新时间：2025-03-21
- “在3D打印检测领域，研究者基于双目结构光原理，建立了三维重构及位姿估计体系，为提高打印精度提供参考。”摘要：In order to realize the detection and control of 3D printed pieces and improve their printing accuracy， the research of 3D reconstruction of 3D parts and position estimation was completed. The system was based on the peripheral scanning visual detection principle of binocular structured light， adopted binocular structured light illumination， and utilized the peripheral scanning imaging mode of a dual-color camera to realize image acquisition and visual calibration through the color and infrared scene at different positions， binocular vision， and scattered structured light depth information. It completed image processing and analysis， such as image fusion， point cloud coloring， multi-frame point cloud alignment fusion， segmentation， etc.， so as to realize the reconstruction of the object field point cloud. The camera position estimation scheme based on the EPNP and ICP algorithms was adopted， with the EPNP algorithm completing the coarse alignment of the reconstructed object scene point cloud and single-view point cloud， while the ICP algorithm completed the fine alignment of the reconstructed object scene point cloud and single-view point cloud to obtain the position estimation of the target. The accuracy of 3D printed pieces’ 3D reconstruction is evaluated by calculating the chamfer distance between the scene point cloud and the standard point cloud， and the average accuracy is 0.675 mm； the accuracy of position estimation is evaluated by the reprojection method， and the average accuracy is 1.669 mm.Through the systematic research， a better evaluation method is provided for the printing inspection of 3D pieces， and a better reference is provided for the subsequent inspection and control of the accuracy of 3D pieces.关键词：Machine Visualization;3D reconstruction;position estimation;image processing;EPNP;ICP0|0|0更新时间：2025-03-21
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